ABB Group May 7, 2010 Slide 1
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1 Roland J. Weiss, Heiko Koziolek, Johannes Stammel, Zoya Durdik, 4 May 2010 Towards Sustainable Industrial Automation Systems Design for Future 2010, Bad Honnef May 7, 2010 Slide 1
2 Towards Sustainable Industrial Automation Systems Agenda Motivation Example Properties of Automation Domain Definition of Long-living Solution Strategies Conclusions May 7, 2010 Slide 2
3 Industrial Automation Systems Market Data Industrial automation systems DCS for process control/manufacturing Total market ~10 BUS$ Industries: oil & gas, utilities, pulp & paper, chemicals, pharmaceutical DCS Five Year Market Analysis and Technology Forecast through 2013 [2009] Sustainability Typical lifetime > 20 years Planned maintenance intervals: ~7 years Maintenance involves HW and SW parts DCS system, including 3rd party components (OS, communication etc) Field devices (sensors, actors) May 7, 2010 Slide 3 Five Year Market Analysis and Technology Forecast through 2012 [2008]
4 Process Control System System Topology Design decisions Engineering & operations combined? Redundancy concept? Service interfaces Technology decisions OS on clients & servers Graphics system (WPF, VB, Java, Flash ) Internal & external communication (field buses, OPC, 61850, RPC, messages ) May 7, 2010 Slide 4
5 Process Control System Server Architecture Real issues Internet Explorer COM VB6 May 7, 2010 Slide 5
6 Industrial Automation Systems Comparison to Other Domains Lifecycle Automation Automotive Aerospace Telecom Business Medical Cost Volume Safety Updates Complexity May 7, 2010 Slide 6 high relevance medium relevance low relevance
7 Definition of Long Living Systems with more than 10 years Changes during lifespan Triggers: Change of Hardware device Change of Communication standards Change of Usage Profile (more/other devices, increased usage behaviour) Dependencies to external technology (high technology stack) Loss of knowledge (team fluctuation, bad knowledge transfer, distributed development) May 7, 2010 Slide 7
8 Leading Questions How to manage evolution? How to manage dependencies? What strategies are there? What is the state of the art? How mature / applicable are approaches? How to guide industrial project managers? How to provide decision support? May 7, 2010 Slide 8
9 How to manage evolution? How to manage evolution? Analytical approaches Solution strategies May 7, 2010 Slide 9
10 Analytical Approaches Architecture-Based Analysis / Description Methods Historical Data, Data Mining applicable in industry? Lehmans Laws Quality Indicators (Metrics, Bad Smells, Dependency Analysis,...) May 7, 2010 Slide 10
11 Solution Strategies Classification / Examples Structural Strategies Architectural Styles / Patterns Reference Architectures Variability Approaches (Software Product Lines) Automation Strategies MDSD approaches (e.g. MDA, Stahl/Völter) Generative Programming (e.g. DSLs) Software Factories Management Strategies Approaches for make or buy decision support (technical and economical aspects) Team organization guidelines Development Process / Environment Decisions Approaches for managing evolution of development environment, e.g. virtualization,... May 7, 2010 Slide 11
12 How to evaluate approaches? Evaluation Criteria Set Ranking Properties: Additional Properties: Applicability (fitting to context) Maturity (industrial experience, tool support) Positive / Negative Perspective Degree of formalization / automation Abstraction Level (code, design, architecture) Development Phase May 7, 2010 Slide 12
13 Conclusion Goal: Synthesize a domain specific method for dealing with evolution Collect / classify solution strategies Apply evaluation criteria Derive guidelines for decision support In-depth evaluation of adapted approaches using case studies May 7, 2010 Slide 13
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